Machine Learning Engineer
- Discuss this with your agent
- Open in Claude
- Open in ChatGPT
Prepare application
- Draft this with your agent
- Open in Claude
- Open in ChatGPT
Role details
Tech stack
+12 more
Job description
Youâll be building AI models that make human-like conversations possible. Youâll work at the intersection of speech, language, and intelligence, taking cutting-edge research and transforming it into real-time, scalable systems that power our core products. Youâll have the unique opportunity to make a huge impact as one of our first ML hires, shaping not only the technology but also the direction of our company. From designing robust models to deploying them in production, youâll own the entire lifecycle of ML systems and help us stay ahead of the curve in AI innovation., + Design, build, and maintain scalable ML systems - from data ingestion and preprocessing to training, testing, and deployment.
- Develop and optimize end-to-end ML pipelines (data collection, labeling, training, validation, monitoring) to ensure reliability and reproducibility.
- Implement robust MLOps practices, including model versioning, experiment tracking, CI/CD for ML, and continuous monitoring in production.
- Collaborate with product and engineering teams to integrate and deploy models into real-time products with a focus on efficiency and scalability.
- Ensure data quality, observability, and performance across all AI systems.
- Stay current with the latest in AI infrastructure, tooling, and research - helping us stay ahead of the curve.
Requirements
- Strong experience in machine learning, deep learning, and NLP.
- Solid background in MLOps and data pipelines - e.g., model deployment, monitoring, and scaling in production environments.
- Proficiency in Python and familiarity with Go.
- Experience with ML lifecycle management tools (e.g., MLflow, Kubeflow, Weights & Biases).
- Ability to design ML systems for robustness, scalability, and automation.
- Strong coding, debugging, and data engineering skills.
- Passion for AI infrastructure and its real-world impact.
- Founder mindset: ownership, independence, and willingness to go deep.
Nice to Have
- Experience in speech recognition, TTS, or audio processing.
- Familiarity with LLMs, generative AI, or real-time inference systems.
- Hands-on experience with data orchestration frameworks (e.g., Airflow, Prefect, Dagster).
- Prior experience in startup environments with fast iteration cycles.
- Knowledge of cloud infrastructure (AWS/GCP/Azure) and containerization tools (Docker, Kubernetes).
Benefits & conditions
- Top-Tier Compensation - Competitive salary + equity in a high-growth startup.
- Comprehensive Benefits - Healthcare, dental, vision coverage.
- Work With the Best - Join a world-class team of engineers and builders Our Operating Principles Extreme Ownership We take full responsibility for our work, outcomes, and team success. No excuses, no blame-shifting - if something needs fixing, we own it and make it better. This means stepping up, even when itâs not âyour job.â If a ball is dropped, we pick it up. If a customer is unhappy, we fix it. If a process is broken, we redesign it. We donât wait for someone else to solve it - we lead with accountability and expect the same from those around us.
About the company
HappyRobot is the infrastructure for enterprises to build and orchestrate AI workforces. Our AI workers donât just communicate - they make decisions, take action, and run operations autonomously across voice, email, and enterprise systems. Born in Y Combinator (S23) and backed by a16z and Base10 with over $60M raised, we power critical operations for global enterprises worldwide. Our platform is battle-tested in the most demanding environments - where AI has real consequences. We started in logistics, built our own voice stack, models, and orchestration layer from the ground up, and are now bringing that infrastructure to every enterprise that runs the real economy. Learn more about our vision in our manifesto., Craftsmanship Putting care and intention into every task, striving for excellence, and taking deep ownership of the quality and outcome of your work. Craftsmanship means never settling for âjust fine.â We sweat the details because details compound. Whether itâs a product feature, an internal doc, or a sales call - we treat it as a reflection of our standards. We aim to deliver jaw-dropping customer experiences by being curious, meticulous, and proud of what we build - even when nobodyâs watching. We are âmajosâ Be friendly & have fun with your coworkers. Always be genuine & honest, but kind. âMajoâ is our way of saying: be a good human. Be approachable, helpful, and warm. Weâre building something ambitious, and itâs easier (and more fun) when we enjoy the ride together. We give feedback with kindness, challenge each other with respect, and celebrate wins together without ego. Urgency with Focus Create the highest impact in the shortest amount of time. Move fast, but in the right direction. We operate with speed because time is our most limited resource. But speed without focus is chaos. We prioritize ruthlessly, act decisively, and stay aligned. We aim for high leverage: the biggest results from the simplest, smartest actions. Weâre running a high-speed marathon - not a sprint with no strategy. Talent Density and Meritocracy Hire only people who can raise the average; âexceptional performance is the passing grade.â Ability trumps seniority. We believe the best teams are built on talent density - every hire should raise the bar. We reward contribution, not titles or tenure. We give ownership to those who earn it, and we all hold each other to a high standard. A-players want to work with other A-players - thatâs how we win. First-Principles Thinking Strip a problem to physics-level facts, ignore industry dogma, rebuild the solution from scratch. We donât copy-paste solutions. We go back to basics, ask why things are the way they are, and rebuild from the ground up if needed. This mindset pushes us to innovate, challenge stale assumptions, and move faster than incumbents. Itâs how we build what others think is impossible. The personal data provided in your application and during the selection process will be processed by Happyrobot, Inc., acting as Data Controller., Empleos similares MACHINE LEARNING ENGINEER 70.000 - 100.000 Time is Brain, SL Barcelona, CataluĂąa Machine Learning Engineer 70.000 - 110.000 Everoad by sennder Barcelona, CataluĂąa Machine Learning Engineer 85.000 - 115.000 sennder Barcelona, CataluĂąa Machine Learning Engineer sennder Technologies Barcelona, Spain Machine Learning Engineer The French Sourcer Madrid Volver a la Ăşltima bĂşsqueda Trabajos ) Machine Learning Engineer ( volver a la Ăşltima bĂşsqueda Recibir ofertas similares por correo electrĂłnico No gracias, llĂŠvame a la oferta de empleo Al crear una alerta, aceptas nuestros TĂŠrminos y condiciones y PolĂtica de privacidad, y el uso de cookies. Inscribirse en esta oferta
Profesiones
- TĂŠcnico
- RecepciĂłnista
- Administrador
- Ventas
- Enfermero
Apply for this position
This job is hosted externally. Click below to view the full posting and apply.
Prepare application
- Draft this with your agent
- Open in Claude
- Open in ChatGPT
Good distractions
Talks and stories from around this role â technically off-topic, practically not.
Moments
Explore playlistsVideos
See allRelated articles
See all
MLOps And AI Driven Development
MLops â Deploying, Maintaining And Evolving Machine Learning Models in Production
What Are Large Language Models?
How to Become an AI Engineer